I build data systems that survive real users, audits, and handover.
Sydney-based Senior Software Engineer and Data & Systems Specialist. Current work spans SQL Server, Power BI, Next.js, secure school data products, applied ML, and agentic AI workflows documented in public.
- 10+ yrs
- shipping software, data, and automation systems
- 2,000 users
- pentested parent portal, shipped solo in 8 weeks ↗
- 200+
- ReviewPulse commits turning coursework into an inspectable NLP lab ↗
- 1,400+
- commits on an open-source agentic study pipeline ↗
Current proof
Recent proof across secure education systems, SQL/Power BI data work, applied ML, and agentic AI workflows documented in public.
Education data products
Secure systems for real school operations
Current work is production-facing: parent access, student-profile views, support workflows, academic reporting, and portal migration support in a regulated school environment.
- Pentested 2,000-parent portal with authorization rechecked at the data boundary.
- Student360-style profile surfaces built around mock/public safety and local-only live-data gates.
- FreshService kiosk and Schoolbox data support shipped with operational handover in mind.
Applied ML systems
Models treated as products, not notebook trophies
Recent ML work focuses on leakage-safe evaluation, model selection, artifact provenance, deployment trade-offs, and interfaces that expose where predictions fail.
- ReviewPulse v3: aspect-based sentiment lab with six model paths and token-level evidence.
- Sommelier API: 22 model/treatment runs before replacing the shipped classifier.
- Churn analysis: optimized for recall and cost trade-offs instead of vanity accuracy.
Agentic AI + security
Agentic AI workflows with public receipts
I use agents to compress throughput, but I document where the human owns judgment: assessment decisions, source truth, defensive controls, and privacy boundaries.
- Public agentic study pipeline: map, notes, compression, active recall, one-pagers, assessment checks.
- Technical reconstruction of the OpenAI-Hugging Face agent incident from public sources.
- Preference for explicit contracts, redaction, auditability, and default-deny thinking.
What I do
Secure education systems
School-facing products and internal tools where authorization, privacy, auditability, and handover are part of the design - not cleanup work after launch.
Data engineering & analytics
SQL Server, Power BI, ETL, and reporting workflows built close to operations: finance, enrolments, academic data, support, and stakeholder dashboards.
Applied ML systems
Models handled like production assets: evaluation contracts, artifact provenance, failure visibility, and interfaces that make trade-offs inspectable.
Agentic AI delivery
Claude Code and Codex workflows used with explicit source truth, review gates, redaction, and public write-ups showing what the agent did and what stayed human-owned.
Core stack
Production systems
Data & analytics
Applied ML
Delivery & agents
Impact
Real, concrete results from systems I've built, scaled, and run - where there's a public write-up, the number links to it.
Scale
2,000
Parents served by a portal built solo in 8 weeks ↗
41,601
Academic rows validated through the Student360 identity bridge
30K+
WhatsApp messages automated / month ↗
Reliability & delivery
Efficiency
100 min → 2 s
Batch job runtime after a rewrite
~2 s
Deploy downtime, down from 10+ minutes ↗
Minutes
Modern academic Excel exports after legacy ETL replacement
Timeline at a glance
Key career milestones and technical achievements
- 2023–2024
Designed and launched Konquista, a Django + Celery/Redis WhatsApp automation platform powering 30K+ monthly messages across all clinics. Expanded Python expertise across FastAPI, Flask, and Streamlit for production-grade ML and automation pipelines.
- 2024
Relocated to Sydney and continued delivering for international clients across time zones. Strengthened backend architecture, designed scalable Python systems, and completed Stanford’s Machine Learning Specialization.
- 2025
Pursuing a Master’s in Software Engineering & AI while expanding full-stack capabilities. Shipped Wedstack (Next.js + GraphQL + Stripe), built AI tools on OpenAI, and published 30+ engineering write-ups on dev.to.
- 2026
Joined St Catherine’s School, Sydney and moved into Data & Systems Specialist work: secure Next.js products, SQL Server pipelines, Power BI reporting, academic-data modernisation, FreshService and Schoolbox support, and Student360-style data surfaces - while completing ML, Deep Learning, and Big Data subjects in the Master’s.